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class Darknet(nn.Module):
"""YOLOv3 object detection model"""
def __init__(self, config_path, img_size=448):
super(Darknet, self).__init__()
self.img_size = img_size
self.seen = 0
self.blocks = []
self.yolo_layers = []
innitial_channel = 1
self.block2 = creat_block_maxpool(3, innitial_channel * 1, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1), pool_kernel=(2, 2), pool_stride=(2, 2))
self.block4 = creat_block_maxpool(innitial_channel * 1, innitial_channel * 2, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1), pool_kernel=(2, 2), pool_stride=(2, 2))
self.block6 = creat_block_maxpool(innitial_channel * 2, innitial_channel * 4, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1), pool_kernel=(2, 2), pool_stride=(2, 2))
self.block8 = creat_block(innitial_channel * 4, innitial_channel * 8, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block9 = nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2), padding=0)
self.block10 = creat_block(innitial_channel * 8, innitial_channel * 16, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block11 = nn.MaxPool2d(kernel_size=(2, 2), stride=(1, 1), padding=0)
self.block12 = creat_block(innitial_channel * 16, innitial_channel * 32, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block13 = creat_block(innitial_channel * 32, innitial_channel * 8, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block14 = creat_block(innitial_channel * 8, innitial_channel * 16, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block15_yolo1 = creat_block(innitial_channel * 16, 3*(5+1), conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
# self.block17 = 13
self.block18 = creat_block(innitial_channel * 8, innitial_channel * 4, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block19 = torch.nn.ConvTranspose2d(innitial_channel * 4, innitial_channel * 8, kernel_size=3, stride=2, padding=0, output_padding=1, bias=True)
# self.block20_rote = 19+8
self.block21 = creat_block(innitial_channel * 8, innitial_channel * 16, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block22 = creat_block(innitial_channel * 16, innitial_channel * 16, conv_kernel=(3, 3), conv_stride=(1, 1), conv_padding=(1, 1))
self.block23_yolo2 = nn.Conv2d(innitial_channel * 16, 3*(5+1), kernel_size=3, stride=1, padding=1)
def forward(self, x):
x2 = self.block2(x)
x4 = self.block4(x2)
x6 = self.block6(x4)
x8 = self.block8(x6)
x9 = self.block9(x8)
x10 = self.block10(x9)
x11 = self.block11(x10)
x12 = self.block12(x11)
x13 = self.block13(x12)
x14 = self.block14(x13)
x15 = self.block15_yolo1(x14)
x18 = self.block18(x13)# return x19 之前的结果运行通过，return x19之后的结果报错。也就是torch.nn.ConvTranspose2d
x19 = self.block19(x18)
# # print(x_8.shape, x_19.shape)
x20 = x8 + x19
x21 = self.block21(x20)
x22 = self.block22(x21)
x23 = self.block23_yolo2(x22)
# return x23 #报错
return x15, x18 #通过rk版本1.4.0--> config model
done
--> Loading model
WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/co ... 7-contrib-sunset.md
* https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.
/usr/local/lib/python3.5/dist-packages/onnx_tf/common/__init__.py:87: UserWarning: FrontendHandler.get_outputs_names is deprecated. It will be removed in future release.. Use node.outputs instead.
warnings.warn(message)
./rknn_models_test2/yoloV3.pt ********************
WARNING: Token 'COMMENT' defined, but not used
WARNING: There is 1 unused token
E Try match aten::_convolution_at_x19.1 ut0 failed, catch exception!
E Catch exception when loading pytorch model: ./rknn_models_test2/yoloV3.pt!
E Traceback (most recent call last):
E File "rknn/base/RKNNlib/converter/convert_pytorch.py", line 1567, in rknn.base.RKNNlib.converter.convert_pytorch.convert_pytorch.match_paragraph_and_param
E File "rknn/base/RKNNlib/converter/convert_pytorch.py", line 1444, in rknn.base.RKNNlib.converter.convert_pytorch.convert_pytorch._torch_try_match_ruler
E ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
E During handling of the above exception, another exception occurred:
E Traceback (most recent call last):
E File "rknn/api/rknn_base.py", line 657, in rknn.api.rknn_base.RKNNBase.load_pytorch
E File "rknn/base/RKNNlib/app/importer/import_pytorch.py", line 104, in rknn.base.RKNNlib.app.importer.import_pytorch.ImportPytorch.run
E File "rknn/base/RKNNlib/converter/convert_pytorch.py", line 1590, in rknn.base.RKNNlib.converter.convert_pytorch.convert_pytorch.match_paragraph_and_param
E File "rknn/api/rknn_log.py", line 312, in rknn.api.rknn_log.RKNNLog.e
E ValueError: Try match aten::_convolution_at_x19.1ut0 failed, catch exception!
Load pytorch model failed!
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